Google’s New Privacy Enhancement Open Source Tools

Google has published two open-source technologies to help companies for processing user data for meeting privacy requirements.

The first one is a tool called Magritte for blurring objects such as license plates in videos. The other is a new version of FHE C++ Transpiler, a privacy tool that Google originally introduced last year. It allows applications to process encrypted datasets without decrypting them first.

Magritte is based on one of Google’s internal software projects. It uses AI to automatically detect when an object containing sensitive data, such as a license plate, appears in a video. Magritte then blurs the object, removing the need for video editing teams to perform the task manually.

The AI features are powered in part by another open-source Google tool called MediaPipe. The latter tool enables developers to build AI applications that can run on devices with limited computing capacity, such as smartphones.

Google also introduced a new version of FHE C++ Transpiler, an open-source tool it originally released last June. The tool makes it easier for developers to implement an encryption technology known as fully homomorphic encryption or FHE.

Enterprise applications store important data in an encrypted form to reduce the risk of cyberattacks. However, the data must be decrypted whenever it needs to be used. Decrypted files are more susceptible to cyberattacks because their contents can be easily accessed by hackers in the event of a breach.

The FHE encryption method on which Google’s FHE C++ Transpiler tool is based removes the need to decrypt data before it’s processed (Homomorphic encryption). As a result, the method allows companies to decrease the risk posed by cyberattacks.

One obstacle is that running FHE software currently requires a prohibitive amount of infrastructure. Another challenge is that the technology is difficult for developers to implement. The tool can analyze a piece of code originally written to process decrypted data and automatically adapt it to run on data encrypted with FHE.

With this, the developers can create applications capable of processing encrypted data with less effort than the task would otherwise require.

FHE C++ Transpiler enhancements

• The optimizations were implemented in the circuits that the tool uses to carry out the processing.
• The size of the circuits FHE Transpiler uses to process data by 50% reduced. As a result, the tool now requires less infrastructure to run and can carry out computations faster.